Towards a unifying diversity-area relationship (DAR) of species- and gene-diversity

AimThe microbiome as a biogeographic entity can be investigated, to the minimum, from two perspectives: one is the spatial/temporal distribution of species (or any level of the operational taxonomic unit or OTU) diversity, and another is the spatial/temporal distribution of metagenomic gene diversity. Both are necessary for comprehensive understanding of the taxonomical, ecological, evolutionary and functional aspects of the microbiome biogeography. Here we propose to investigate the metagenomic diversity-area relationship (m-DAR), which is a transformation of the species-DAR (s-DAR) that extended the classic SAR (species-area relationship) by replacing the species richness with general species diversity measured in Hill numbers. InnovationThe m-DAR and s-DAR, using the same mathematical models, offer a unifying tool for investigating the biogeography of microbiome from ecological, metagenomic and functional perspectives. Specifically, we investigate m-DAR of the human gut metagenome in terms of the MG (metagenomic gene) and MFGC (metagenome functional gene cluster) respectively, by sketching out the DAR-profile, PDO (pair-wise diversity overlap) profile, MAD (maximal accrual diversity) profile, and RIP (ratio of individual- to population-diversity) profile at each scale. These profiles constitute our unifying DAR toolset and can be applied to any microbiomes beyond the human gut microbiome. Main conclusionsWe demonstrate the construction and applications of the m-DAR and its associated four profiles with six large datasets of the human gut metagenomes including three microbiome-associated diseases (obesity, diabetes, IBD) and their healthy controls, supported with randomization tests to determine the differences between healthy and diseased treatments in their m-DAT parameters. Theoretically, our study presents a successful case to demonstrate the feasibility of unifying systematic biogeography vs. evolutionary biogeography, of an inclusive biogeography of plants, animal and microbes. Practically, our approach offers an important tool for investigating the spatial scaling of human metagenome diversity in a population (cohort) and its relationship with individual-level diversity.